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Bioinformatics Algorithms
Techniques and Applications
Ion Mandoiu (Edited by), I Mandoiu (Author), Alexander Zelikovsky (Edited by), Yi Pan (Series edited by), Albert Y. Zomaya (Series edited by)
9780470097731, Wiley
Hardback, published 28 March 2008
528 pages
24.3 x 16.1 x 3 cm, 0.862 kg
"This clear and approachable presentation makes the book appropriate for researchers, practioners, and graduate students." (Mathematical Reviews, Issue 2009b) "This volume will be a nice addition to the bioinformatician's bookshelf." (Quarterly Review of Biology, December 2008)
Presents algorithmic techniques for solving problems in bioinformatics, including applications that shed new light on molecular biology This book introduces algorithmic techniques in bioinformatics, emphasizing their application to solving novel problems in post-genomic molecular biology. Beginning with a thought-provoking discussion on the role of algorithms in twenty-first-century bioinformatics education, Bioinformatics Algorithms covers: General algorithmic techniques, including dynamic programming, graph-theoretical methods, hidden Markov models, the fast Fourier transform, seeding, and approximation algorithms Algorithms and tools for genome and sequence analysis, including formal and approximate models for gene clusters, advanced algorithms for non-overlapping local alignments and genome tilings, multiplex PCR primer set selection, and sequence/network motif finding Microarray design and analysis, including algorithms for microarray physical design, missing value imputation, and meta-analysis of gene expression data Algorithmic issues arising in the analysis of genetic variation across human population, including computational inference of haplotypes from genotype data and disease association search in case/control epidemiologic studies Algorithmic approaches in structural and systems biology, including topological and structural classification in biochemistry, and prediction of protein-protein and domain-domain interactions Each chapter begins with a self-contained introduction to a computational problem; continues with a brief review of the existing literature on the subject and an in-depth description of recent algorithmic and methodological developments; and concludes with a brief experimental study and a discussion of open research challenges. This clear and approachable presentation makes the book appropriate for researchers, practitioners, and graduate students alike.
Preface ix Contributors xi 1 Educating Biologists in the 21st Century: Bioinformatics Scientists versus Bioinformatics Technicians 1 Part I Techniques 7 2 Dynamic Programming Algorithms for Biological Sequence and Structure Comparison 9 3 Graph Theoretical Approaches to Delineate Dynamics of Biological Processes 29 4 Advances in Hidden Markov Models for Sequence Annotation 55 5 Sorting- and FFT-Based Techniques in the Discovery of Biopatterns 93 6 A Survey of Seeding for Sequence Alignment 117 7 The Comparison of Phylogenetic Networks: Algorithms and Complexity 143 Part II Genome and Sequence Analysis 175 8 Formal Models of Gene Clusters 177 9 Integer Linear Programming Techniques for Discovering Approximate Gene Clusters 203 10 Efficient Combinatorial Algorithms for DNA Sequence Processing 223 11 Algorithms for Multiplex PCR Primer Set Selection with Amplification Length Constraints 241 12 Recent Developments in Alignment and Motif Finding for Sequences and Networks 259 Part III Microarray Design and Data Analysis 277 13 Algorithms for Oligonucleotide Microarray Layout 279 14 Classification Accuracy Based Microarray Missing Value Imputation 303 15 Meta-Analysis of Microarray Data 329 Part IV Genetic Variation Analysis 353 16 Phasing Genotypes Using a Hidden Markov Model 355 17 Analytical and Algorithmic Methods for Haplotype Frequency Inference: What Do They Tell Us? 373 18 Optimization Methods for Genotype Data Analysis in Epidemiological Studies 395 Part V Structural and Systems Biology 417 19 Topological Indices in Combinatorial Chemistry 419 20 Efficient Algorithms for Structural Recall in Databases 439 21 Computational Approaches to Predict Protein–Protein and Domain–Domain Interactions 465 Index 493
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Subject Areas: Electronics & communications engineering [TJ]
